Equipment monitoring devices are of fundamental importance to modern engineering. Increasingly, data taken from machines in operation is compared with models generated from earlier data taken from the same or similar machines to assure compliance with design specifications and to predict future performance. In large, complex machines such predictive models tend to be based on data gathered through painstaking experimentation during which machine operating conditions are systematically varied while machine outputs are recorded. Particularly when a machine is initially deployed, there may be little or no historical data available with which to predict machine responses to changes in machine operating conditions. A significant amount of historical data may be required in order to establish models useful in machine monitoring devices.
There is a need for machine monitoring devices which are capable of establishing useful predictive models with limited data, and which can alert operators to potential deviations from acceptable machine performance based on outputs of the predictive models.